How can environmental regulators use information on 48-hour toxicity tests to predict the effects of a few minutes of pollution? Or, at the other extreme, what is the relevance of 96-hour toxicity data for organisms that may have been exposed to a pollutant for six months or more? Time to event methods are the key to answering these types of questions.
Risk Assessment with Time to Event Models is the first comprehensive treatment of these methods in the context of ecological risk assessment. Leading experts from industry, academia, and government regulatory agencies explain how these methods can be used to extract more useful information from laboratory data than is present in simple summary statistics like 48-h LC50.
The book offers a clear introduction to the field through several approaches, from the introductory to the more mathematical. Risk Assessment with Time to Event Models demonstrates the relevance of time in the analysis and reporting of toxicity data through the use of practical examples from the field of environmental toxicology. It also incorporates helpful analogies from other disciplines that commonly use time to event modeling.
Introduction to time to event methods 1(6) Michael C. Newman Mark Crane Time to event analysis of standard ecotoxicity data 7(16) Mark Crane Albania Grosso Applying time to event methods to assess pollutant effects on populations 23(16) Michael C. Newman John T. McCloskey Time-concentration-effect models in predicting chronic toxicity from acute toxicity data 39(30) Foster L. Mayer Mark R. Ellersieck Gary F. Krause Kai Sun Gunhee Lee Denny R. Buckler Just how much better is a time to event analysis? 69(20) Philip M. Dixon Using time to event modeling to assess the ecological risk of produced water discharges 89(14) Chris C. Karman Time to event analysis in the agricultural sciences 103(18) John S. Fenlon Time to event analysis in ecology 121(20) Bryan F.J. Manly Time to event analysis in engineering 141(12) Alan Kimber Can risk assessment be improved with time to event models? 153(14) Mark Crane Peter F. Chapman Tim Sparks John Fenlon Michael C. Newman Conclusions 167(4) Mark Crane Peter F. Chapman Michael C. Newman Index 171
Mark Crane, Michael C. Newman, Peter F. Chapman, John S. Fenlon
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